Multivariate Splines and Their Applications

Fuente: arXiv
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Autor principal: Lai, Ming-Jun
Formato: Preprint
Publicado: 2024
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author Lai, Ming-Jun
author_facet Lai, Ming-Jun
contents This paper begins by reviewing numerous theoretical advancements in the field of multivariate splines, primarily contributed by Professor Larry L. Schumaker. These foundational results have paved the way for a wide range of applications and computational techniques. The paper then proceeds to highlight various practical applications of multivariate splines. These include scattered data fitting and interpolation, the construction of smooth curves and surfaces, and the numerical solutions of various partial differential equations, encompassing both linear and nonlinear PDEs. Beyond these conventional and well-established uses, the paper introduces a novel application of multivariate splines in function value denoising. This innovative approach facilitates the creation of LKB splines, which are instrumental in approximating high-dimensional functions and effectively circumventing the curse of dimensionality.
format Preprint
id arxiv_https___arxiv_org_abs_2401_08423
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Multivariate Splines and Their Applications
Lai, Ming-Jun
Numerical Analysis
41-02, 41A10, 41A15, 65-02, 65D05, 65D10, 65D17
This paper begins by reviewing numerous theoretical advancements in the field of multivariate splines, primarily contributed by Professor Larry L. Schumaker. These foundational results have paved the way for a wide range of applications and computational techniques. The paper then proceeds to highlight various practical applications of multivariate splines. These include scattered data fitting and interpolation, the construction of smooth curves and surfaces, and the numerical solutions of various partial differential equations, encompassing both linear and nonlinear PDEs. Beyond these conventional and well-established uses, the paper introduces a novel application of multivariate splines in function value denoising. This innovative approach facilitates the creation of LKB splines, which are instrumental in approximating high-dimensional functions and effectively circumventing the curse of dimensionality.
title Multivariate Splines and Their Applications
topic Numerical Analysis
41-02, 41A10, 41A15, 65-02, 65D05, 65D10, 65D17
url https://arxiv.org/abs/2401.08423